Data Scientist
MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD. · Singapore ·
- Category
- Data science
MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD. · Singapore ·
Responsibilities and Tasks
Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes.
Agentic AI and LLM Development:
Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization.
Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications.
Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments.
Optimize for performance, latency, and token efficiency.
Collaborate with senior team members on testing, deployment, and monitoring.
Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders
Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness,exercising sound judgment and complying with organizational standards and legal requirements.
Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
Required Qualifications & Skills
Education/Experience:
Bachelor's in Computer Science, Data Science, Operations Research, Mathematics, or equivalent.
Strong desire to grow a career as a Data Scientist in advanced, highly automated industrial manufacturing.
Solid foundation in statistics and/or machine learning (supervised/unsupervised learning, model evaluation, feature engineering).
Experience with SQL for data extraction and manipulation.
Experience with version control (Git).
Familiarity with building interactive data applications or dashboards (e.g., Streamlit, PowerBI, or similar).
Strong verbal and written communication skills, with the ability to explain complex analytical results clearly.
Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes.